Quantum-Resistant Secure Communication Protocol for Digital Twin-Enabled Context-Aware IoT-Based Healthcare Applications
Basudeb Bera, Ashok Kumar Das, Biplab Sikdar
Abstract
Digital Twins (DTs) play a crucial role in context-aware Internet of Things (IoT) applications within the healthcare sector, including the industrial healthcare domain, by facilitating the continuous sharing of sensitive and confidential patient data from physical objects in real time. This shared data is essential for treatment planning and decision-making processes, often being accessed remotely by authorized users. However, traditional security mechanisms, which rely on the integer factorization problem (IFP) and the elliptic curve discrete logarithm problem (ECDLP), are vulnerable to quantum attacks using algorithms like Shor's, posing significant risks to data protection. As a result, the healthcare sector faces several security challenges, including the vulnerability of sensitive patient data to cyberattacks, quantum threats, the risk of unauthorized access to medical devices and IoT systems, and the increasing sophistication of cybercriminals exploiting weak authentication methods. To address these issues, we propose a quantum-resistant protocol that safeguards data privacy in DT-enabled IoT healthcare applications, ensures secure transmission of information, maintains patient trust, supports long-term data confidentiality, and protects medical devices and IoT systems from potential breaches. By employing lattice-based cryptographic techniques, particularly the ring learning with errors (RLWE) problem, the proposed scheme effectively addresses contemporary security challenges, including those posed by quantum computing. Real-time experiments conducted on Raspberry Pi 4 devices, along with computational overhead analysis, demonstrate the protocol's efficiency. Additionally, formal security validation using the Scyther tool and security analysis with the RoR model reinforce the robustness of the proposed protocol. A comprehensive comparative evaluation against existing schemes highlights its lightweight, scalable, and efficient nature. Furthermore, performance evaluations in the context of unknown attacks show that the proposed scheme significantly outperforms current alternatives in terms of effectiveness.